基于scala 新版API操作HBase

package com.sncfi.hbaseimport org.apache.hadoop.hbase.client.HBaseAdminimport org.apache.hadoop.hbase.client.Adminimport org.apache.hadoop.hbase.util.Bytesimport org.apache.hadoop.hbase.{HBaseConfiguration,HTableDescriptor,TableName,HColumnDescriptor}import org.apache.hadoop.hbase.mapreduce.TableInputFormatimport org.apache.spark.SparkConfimport org.apache.spark.SparkContextimport org.apache.hadoop.hbase.client.ConnectionFactoryimport org.apache.hadoop.hbase.client.Connectionimport org.apache.hadoop.hbase.client.Putimport org.apache.hadoop.hbase.client.Getimport org.apache.hadoop.hbase.client.Deleteimport org.apache.hadoop.hbase.client.Tableimport org.apache.hadoop.hbase.client.Scanimport org.apache.hadoop.hbase.client.ResultScannerimport org.apache.hadoop.hbase.client.Result/**  * Created by admin on 2016/12/14.  * 这是一个spark自带一个hbase例子  * 在这里要注意的是，自定义方法要写在前面。  */object HBaseLocalTest {  //创建表  def createHTable(connection: Connection,tablename: String): Unit=  {    //Hbase表模式管理器    val admin = connection.getAdmin    //本例将操作的表名    val tableName = TableName.valueOf(tablename)    //如果需要创建表    if (!admin.tableExists(tableName)) {      //创建Hbase表模式      val tableDescriptor = new HTableDescriptor(tableName)      //创建列簇1    artitle      tableDescriptor.addFamily(new HColumnDescriptor("artitle".getBytes()))      //创建列簇2    author      tableDescriptor.addFamily(new HColumnDescriptor("author".getBytes()))      //创建表      admin.createTable(tableDescriptor)      println("create done.")    }  }  //删除表  def deleteHTable(connection:Connection,tablename:String):Unit={    //本例将操作的表名    val tableName = TableName.valueOf(tablename)    //Hbase表模式管理器    val admin = connection.getAdmin    if (admin.tableExists(tableName)){      admin.disableTable(tableName)      admin.deleteTable(tableName)    }  }  //插入记录  def insertHTable(connection:Connection,tablename:String,family:String,column:String,key:String,value:String):Unit={    try{      val userTable = TableName.valueOf(tablename)      val table=connection.getTable(userTable)      //准备key 的数据      val p=new Put(key.getBytes)      //为put操作指定 column 和 value      p.addColumn(family.getBytes,column.getBytes,value.getBytes())      //验证可以提交两个clomun？？？？不可以     // p.addColumn(family.getBytes(),"china".getBytes(),"JAVA for china".getBytes())      //提交一行      table.put(p)    }  }  //基于KEY查询某条数据  def getAResult(connection:Connection,tablename:String,family:String,column:String,key:String):Unit={    var table:Table=null    try{      val userTable = TableName.valueOf(tablename)       table=connection.getTable(userTable)      val g=new Get(key.getBytes())      val result=table.get(g)      val value=Bytes.toString(result.getValue(family.getBytes(),column.getBytes()))      println("key:"+value)    }finally{      if(table!=null)table.close()    }  }  //删除某条记录  def deleteRecord(connection:Connection,tablename:String,family:String,column:String,key:String): Unit ={    var table:Table=null    try{      val userTable=TableName.valueOf(tablename)      table=connection.getTable(userTable)      val d=new Delete(key.getBytes())      d.addColumn(family.getBytes(),column.getBytes())      table.delete(d)      println("delete record done.")    }finally{      if(table!=null)table.close()    }  }  //扫描记录  def scanRecord(connection:Connection,tablename:String,family:String,column:String): Unit ={    var table:Table=null    var scanner:ResultScanner=null    try{      val userTable=TableName.valueOf(tablename)      table=connection.getTable(userTable)      val s=new Scan()      s.addColumn(family.getBytes(),column.getBytes())      scanner=table.getScanner(s)      println("scan...for...")      var result:Result=scanner.next()      while(result!=null){        println("Found row:" + result)        println("Found value: "+Bytes.toString(result.getValue(family.getBytes(),column.getBytes())))        result=scanner.next()      }    }finally{      if(table!=null)        table.close()        scanner.close()    }  }  def main(args: Array[String]): Unit = {  // val sparkConf = new SparkConf().setAppName("HBaseTest")    //启用spark上下文，只有这样才能驱动spark并行计算框架   //val sc = new SparkContext(sparkConf)    //创建一个配置，采用的是工厂方法    val conf = HBaseConfiguration.create    val tablename = "blog"    conf.set("hbase.zookeeper.property.clientPort", "2181")    conf.set("zookeeper.znode.parent", "/hbase-unsecure")    conf.set("hbase.zookeeper.quorum", "hadoop36.newqd.com,hadoop37.newqd.com,hadoop38.newqd.com")   // conf.set("hbase.zookeeper.quorum", "hadoop1.snnu.edu.cn,hadoop3.snnu.edu.cn")    conf.set(TableInputFormat.INPUT_TABLE, tablename)    try{      //Connection 的创建是个重量级的工作，线程安全，是操作hbase的入口      val connection= ConnectionFactory.createConnection(conf)      //创建表测试      try {        createHTable(connection, "blog")        //插入数据,重复执行为覆盖        insertHTable(connection,"blog","artitle","engish","002","c++ for me")        insertHTable(connection,"blog","artitle","engish","003","python for me")        insertHTable(connection,"blog","artitle","chinese","002","C++ for china")        //删除记录       // deleteRecord(connection,"blog","artitle","chinese","002")        //扫描整个表        scanRecord(connection,"blog","artitle","engish")        //删除表测试       // deleteHTable(connection, "blog")      }finally {        connection.close     //   sc.stop      }    }  }}